AIDec 16, 2015

Solving stable matching problems using answer set programming

arXiv:1512.05247v1
Originality Incremental advance
AI Analysis

This provides a flexible solution for researchers and practitioners dealing with stable matching variants, though it is incremental as it builds on existing ASP methods.

The authors tackled the need for new algorithms for each variant of the stable marriage problem by proposing an answer set programming encoding that can be adapted for various applications, resulting in the first exact implementation for finding optimal stable matchings under criteria like sex-equality and minimum regret.

Since the introduction of the stable marriage problem (SMP) by Gale and Shapley (1962), several variants and extensions have been investigated. While this variety is useful to widen the application potential, each variant requires a new algorithm for finding the stable matchings. To address this issue, we propose an encoding of the SMP using answer set programming (ASP), which can straightforwardly be adapted and extended to suit the needs of specific applications. The use of ASP also means that we can take advantage of highly efficient off-the-shelf solvers. To illustrate the flexibility of our approach, we show how our ASP encoding naturally allows us to select optimal stable matchings, i.e. matchings that are optimal according to some user-specified criterion. To the best of our knowledge, our encoding offers the first exact implementation to find sex-equal, minimum regret, egalitarian or maximum cardinality stable matchings for SMP instances in which individuals may designate unacceptable partners and ties between preferences are allowed. This paper is under consideration in Theory and Practice of Logic Programming (TPLP).

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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